One of the best parts of my job at Google is 20 percent time. While I was hired to help developers use Google’s APIs, I value the time I’m afforded to be a student myself—to learn new technologies and solve real-world problems. A few weeks prior to the recent Australian election an opportunity presented itself. A small team in Sydney set their sights on helping the 15 million voters stay informed of how to participate, track real-time results, and (of course) find the closest election sausage sizzle!

Our team of designers, engineers and product managers didn’t have an immediate sense of how to attack the problem. What we did have was the power of Google’s APIs, programming languages, and Cloud hosting with Firebase and Google Cloud Platform.

The result is a mish-mash of some technologies we’d been wanting to learn more about. We’re open sourcing the ausvotes.withgoogle.com repository to give developers a sense of what happens when you get a handful of engineers in a room with a clear goal and a immovable deadline.

Editor’s note: Today’s guest post is from Daniel Viveiros, Head of Technology at CI&T, a Google Cloud Platform Partner of the Year LATAM 2013. In this post, Daniel describes how CI&T in partnership with Coca-Cola built the ‘Happiness Flag’ for the Coca-Cola 2014 FIFA World Cup™ campaign in Brazil. To learn more about the Happiness flag visit this website.

As part of the ‘The World’s Cup’ campaign, Coca-Cola wanted to do something that would visually illustrate soccer’s global reach. Coca-Cola invited fans around the world to share their photos to create the Happiness Flag — the world’s largest mosaic flag crafted from thousands of crowdsourced images submitted by people in more than 200 countries. The flag, 3,015 square meters in size, was unveiled during the opening ceremony of the 2014 FIFA World Cup™.

A project of this scale calls for high performing and reliable technology, so when we started working with Coca-Cola to build the infrastructure for the Happiness Flag campaign, we knew we had to use Google Cloud Platform. By using Google Cloud Platform, we turned a big, innovative idea into reality on a global scale.

To create the Happiness Flag, we leveraged the whole Google Cloud Platform stack as shown below:

Google App Engine enabled us to handle the computing workload, capable of handling millions of images via Twitter, Facebook, Instagram and email, to the searches for images and view requests. The architecture was scalable to meet this kind of transaction demand and the fluctuations in traffic. We stored all the images in Google Cloud Storage, where integrated edge caching support and image services made it an ideal choice for serving the images. Meanwhile, Google Compute Engine gave us the capability for long-running processes, such as the Twitter integration and advanced image transformations. We were able to show how powerful the creation of hybrid environments can be, using both Platform-as-a-Service (Google App Engine) and raw virtual machines (Google Compute Engine) in the cloud.

We used other out-of-the-box Google Cloud Platform technologies like Memcache, Datastore and Task Queues to ensure outstanding levels of performance and scalability. We know that many fans will be viewing the Happiness Flag on their mobile devices, so we needed a platform that would offer different capacities of computational power. The system provides amazing user experience with high performance and low latency, regardless of the device and its location. Using Google Cloud Platform, the campaign runs smoothly 24/7 and includes redundancy, failover techniques, backups and state-of-the-art monitoring. Plus, it’s affordable.

After the physical flag was unveiled before the opening match, the digital mosaic was made available with a Google map-like zoom in and out with eleven levels of detail. Anyone who submitted an image can now search for themselves on the virtual flag and the search results will show up as pins in the mosaic, like locations found in a Google map. By clicking on the pin, their photos open up in an overlay and they are taken to the maximum level of zoom in to see the “neighborhood” around their image in the flag. After the match, a link to the Happiness Flag site was sent to each participant as a souvenir.

Our goal was to help Coca-Cola create a project that would celebrate the 2014 FIFA World Cup™ by enabling fans from all over the world to express their creativity in a show of unity and art. What better way to open the games than by displaying the Happiness Flag, which is a symbol of the spirit of the game and its fans.

Editor’s note: Today’s guest post is from Jeff Trom, CTO at Webfilings, a Software-as-a-Service provider that develops cloud-based solutions for business reporting.

At Webfilings, we’re reinventing complex business reporting. Wdesk, our flagship product, is an enterprise solution that is transforming how companies manage and report complex business data. It’s a collective workspace for teams to come together to build documents and reports without having to go to IT for assistance. Using Wdesk, financial teams have quickly become accustomed to how the cloud has simplified collaboration, provided global accessibility and eliminated the replication of data and documents.

What started as an idea to automate SEC reporting has now grown to a robust offering that supports more than 60% of the Fortune 500 in just 4 years since launch. We’ve been able to build a great company and culture where rapid innovation and best-in-class customer service are key.

We rely on Google Cloud Platform to make a formerly onerous process seem easy. Cloud Platform replicates our terabytes of data across multiple datacenters seamlessly and allows our developers to focus on innovation, not infrastructure. We deploy updates daily and leverage Google App Engine’s ability to simultaneously serve traffic from multiple versions to test new features with a few customers before releasing them to everyone. This helps ensure that our customers have the best experience possible each time they log in to Wdesk. Check out the video below to learn more about how we’re using Cloud Platform.

In our product space, the data-in-motion architecture we’ve chosen is what sets us apart. It requires:

Editor’s note: Today’s guest blog comes from Dan Mesh, Vice President of Technology at Evite, the pioneer in online invitations and social planning. Evite has over 30 million registered users and sends more than 250 million party invitations annually.

In the past year, we’ve introduced a couple of exciting new products at Evite: our Postmark service offers premium online invitations and announcements for milestone events like weddings and births, and Evite Ink lets our users design custom paper invitations that we print and mail for a small fee. We couldn’t have launched these products without Google Compute Engine and Google App Engine, which gave us the infrastructure needed to scale our services to high demands and analyze large volumes of data they generate.

Evite has been around since 1998, but behind this well-known online brand is a small and lean team. Migrating to the cloud has allowed us to focus our time, energy and financial resources on development of new products and services, free from worries of server management, capacity planning and hardware costs.

We chose Google Cloud Platform because the combination of App Engine and Compute Engine truly delivers on the cloud’s promise of scalable and elastic computing. App Engine’s autoscaling means that as long as our applications are developed in line with the platform API’s and architecture guidelines, scalability comes for free. This is a huge benefit since we no longer worry about scaling our services to meet heavy demands and are also free from the difficulties and risks inherent in capacity planning.

Most online businesses have very consistent daily, weekly and seasonal traffic patterns, and in Evite’s case, these patterns are even more pronounced. In the past, we used to provision resources to meet peak demand allowing for a healthy margin of error and future growth. Naturally, this resulted in a lot of wasted capital and engineering resources. Now that most of our systems are running on Google Cloud Platform, we see significant savings as application servers expand and shrink elastically in accordance with our web traffic.

For example, in the past Evite was hesitant to roll out major application releases in Q4, typically the busiest time of the year for us. During this time, we reach our peak traffic, and operational focus was on making sure nothing went wrong. Any significant releases represented unwanted risk. Cloud Platform greatly simplifies the release process and provides built-in traffic splitting. This has made it possible for Evite product teams to test new features and release products more frequently and with reduced risks, even during the busiest times of year.

As we add new products and services, Compute Engine plays a key role in our application infrastructure. We use it to closely monitor and analyze the performance of our products and services. All application data and log files generated by applications running on App Engine flow through a cluster of Compute Engine instances running extract, transform, load (ETL) processes, which feed this data into the data warehouse. There we analyze the collected data to detect errors and usage patterns helping us improve the design of our products and maintain performance levels.

Compute Engine gets high marks for interoperability with App Engine and other cloud vendors. We use AWS Redshift as our data warehouse so interoperability is very important. Equally impressive are predictable, high I/O performance and fast instance startup times. For our data processing workloads these two metrics are critical to success.

With App Engine powering all of our customer-facing services and Compute Engine helping us monitor and understand application performance, Evite is in great shape to create and release new products. We look forward to many new releases in 2014 knowing we can count on Cloud Platform to make these launches trouble-free.

Editor’s note: Today we hear from Daniel Hasselberg, co-founder and chief executive officer of mobile game development company, MAG Interactive, based in Stockholm, Sweden. MAG Interactive produces some of the most popular games in the world, including Ruzzle, which has more than 45 million players in 142 different countries.

When we launched our word game Ruzzle in 2012, we had no idea it would become an international sensation almost overnight. We initially promoted the game only to our family and friends, but within two weeks of our launch, Ruzzle was the No.1 game on the Swedish App Store.

I believe if we hadn’t used Google App Engine to build the backend of Ruzzle, we wouldn’t have been able to scale fast enough with our own servers, which would have killed the app in the marketplace. There were about a million downloads of Ruzzle per month in the Nordic region, Holland, Spain and Italy through 2012. As we refined the game’s social integration through channels like Facebook and Twitter, we grew rapidly in Italy and the United States. In 2013, Ruzzle became the No. 1 game download on Google Play and the App Store in Italy, Sweden, the United States and many other countries.

Things were especially crazy at the end of last year. We were seeing about 700,000 new players each day from December 2012 through January 2013. We added 20 million users in a single month! It was incredible to see App Engine scale – and just keep on working – as we grew from about 5 million players to 25 million players in just a few weeks.

Our decision to use App Engine as the platform for Ruzzle and our new game, QuizCross, was strategic. Some of us at MAG Interactive helped develop the server platform for one of the most popular music download services in the Nordic region, so we knew about the challenges of having to scale quickly. While we didn’t anticipate Ruzzle’s popularity, we did recognize even before creating the game that we could face scaling problems if we were successful. So we decided from day one to use a cloud solution.

We looked at Amazon’s platform but preferred Google’s approach to cloud solutions. Google’s scalability was an important factor in our decision, but we also appreciated the company’s transparent pricing. The more efficient we became with App Engine, the less we paid.

The Google Cloud Platform team has been great to work with, as well. They are very supportive and appreciate our feedback. The technical support experts at Google are amazing, too – very hands-on. They know the platform extremely well and can help us work through any challenge.

We’re also using Google BigQuery for business intelligence. We track millions of events in the game every day so we know what users are doing – or not doing – and how we should improve the experience. We really like that we can throw enormous amounts of data at BigQuery, and it still performs. It only takes a few seconds to get results, and there are no scaling issues. It’s also easy to use. We have just one data analyst doing all the work with BigQuery but could probably use more people. If there are a few brilliant data mining experts out there who can imagine a future in Stockholm, please give us a call!

One thing we’ve learned from our BigQuery analysis is that the more users play Ruzzle, the more they improve their skills. New players typically find about 18 words in the two-minute time frame they’re given. After they play 100 games, they can find about 50 words, on average. I think that tracking player improvement is what keeps people playing and has helped to make Ruzzle so popular.

BigQuery offers our company a lot of insight into the use of our games and how we can improve them. We’re looking forward to expanding our relationship with Google as App Engine and Cloud Platform evolves.

3 weeks following our last release, the App Engine team is happy to announce 1.7.7. We plan to deliver our Google I/O release next month.

Outbound sockets moved to PreviewOutbound sockets is now in preview in this release for Java and Python. With outbound sockets, billing-enabled App Engine applications can now make outbound connections with TCP or UDP sockets. This allows developers to build applications that weren’t previously possible on App Engine, such as IMAP or DNS clients.

In the Python runtime, we’ve added support for the Python SSL Library, so you can now open secure connections to remote services such as Apple’s Push Notification service. Similarly, Java developers can now use the javax.net.ssl package to make outbound SSL connections.

Java 7 runtime upgraded to General Availability

The App Engine team is committed to quickly releasing features to General Availability. You may recall we announced that the Java 7 runtime was in preview just 2 months ago. Since then we have seen 200% adoption week over week, and today are happy to announce the General Availability of the runtime.

In order to help developers move over, all app deployments initiated using the new 1.7.7 SDK will use Java 7 unless you explicitly opt out with a command line flag. In the near future, we plan to automatically update all existing Java 6 applications to Java 7. Most applications shouldn’t be affected by this change, but we encourage you to start testing your application in advance. For more compatibility information, we suggest that you check out the Java SE 7 and JDK 7 Compatibility notes.

We’re happy to announce that billing-enabled applications will no longer be required to spend a minimum of $2.10 per week. This means that you can enable billing for a free tier application and continue running within the free tier without concern that a spike in traffic will terminate serving (note that you can always specify a daily dollar budget). The minimum spend was originally intended to prevent abuse and ensure that we can offer a stable, reliable system with a free tier. We have determined that we can continue to support the free tier, without relying on the minimum spend. So, goodbye $2.10!

A key benefit of running on a managed service like App Engine is the changes that occur behind the scenes that automatically improve the performance of your applications. In just the past two months, we’ve made many such improvements:

Faster and more consistent deployments. Many customers are seeing up to 10x reductions in time to deploy a new application version.

We have fully deployed an entirely new scheduler system which autoscales applications more smoothly and efficiently.

Admin console dashboard charts and current load/error reports have moved to a new, more reliable backend

The release version of App Engine is now visible in the Admin Console and in request logs

Several stability and scheduling improvements to Task Queue

The complete list of features and bug fixes for 1.7.7 can be found in ourrelease notes. For App Engine coding questions and answers check us out onStack Overflow, and for general discussion and feedback, find us on ourGoogle Group.

In the nine months since announcing Compute Engine, customers have been using Google’s Infrastructure as a Service product and giving us valuable feedback. Sebastian Stadil of Scalr wrote, in a recent review:

“Google Compute Engine is not just fast. It’s Google fast. In fact, it’s a class of fast that enables new service architectures entirely.”

We’re happy to hear that, because one of our main goals in building Compute Engine is to enable a new generation of applications with direct access to the capabilities of Google’s vast computing infrastructure.

Based on user feedback, we’ve added a number of major features including:

Two new supported zones in Europe, which provide lower latency and higher performance for our European customers. We’ve also made it easy to migrate virtual machine instances from one zone to another via an enhancement to our gcutil command line tool.

An enhanced metadata server, with the ability to support recursive queries, blocking gets and selectable response formats, along with support for updating virtual machine tags and metadata on running instances (which enables dynamic reconfiguration scenarios).

While we’ve been hard at work developing new features, we’ve also had the opportunity to play. Check out the amazing World Wide Maze Chrome Experiment, developed by the Chrome team in Japan. This game converts any web site of your choice into an interactive, three dimensional maze, navigated remotely via your smartphone. Compute Engine virtual machines run Node.js to manage the game state and synchronization with the mobile device, while Google App Engine hosts the game’s web UI. This application provides an excellent example of the new kinds of rich, high performance back end services enabled by Google Cloud Platform.

With today’s announcement, we look forward to welcoming many new customers, and bringing exciting new applications to Google Cloud Platform!

Have you ever wanted to integrate SMS or voice communications into your app? We’ve been working with our friends over at Twilio to make it easier to do so. Today we’re announcing native Python and Java libraries for working with Twilio APIs onto Google Cloud Platform.

Last year weinvited proposals for innovative projects built on Google’s infrastructure. Today we are pleased to announce the 11 recipients of aGoogle App Engine Education Award. Professors and their students are using the award in cloud computing courses to study databases, distributed systems, web mashups and to build educational applications. Each selected project received $1000 in Google App Engine credits.

Awarding computational resources to classroom projects is always gratifying. It is impressive to see the creative ideas students and educators bring to these programs.

Below is a brief introduction to each project. Congratulations to the recipients!

Project description: The objective of this undergraduate database systems course is for students to implement one database application in two technology stacks, a traditional relational database and on Google App Engine. Students are asked to study both models and provide concrete comparison points.

The goal of the project is to allow the students to learn distributed system concepts by developing real distributed system management systems and testing them on real world cloud computing infrastructures such as Google App Engine.

Project description:A graduate-level course that will be offered in Fall 2013 on the design and implementation of large data management system kernels. The objective is to integrate features from a relational database engine with some of the new features from NoSQL systems to enable efficient and scalable data management over a cluster of commodity machines.

Project description:TeacherTap is a free, simple classroom-response system built on Google App Engine. It lets students give instant, anonymous feedback to teachers about a lecture or discussion from any computer or mobile device with a web browser, facilitating more adaptive class sessions.

Project description:Topics in Computer Science: Web Mashups. A CS2 course that combines Google App Engine and MIT App Inventor. Students will learn to build apps with App Inventor to collect data about their life on campus. They will use Google App Engine to build web services and apps to host the data and remix it to create web mashups. Offered in the 2013 Spring semester.

Project description: Cloud Computing for Scientific Applications — Autonomic Cloud Computing teaches students how a hybrid HPC/Grid + Cloud cyber infrastructure can be effectively used to support real-world science and engineering applications. The goal of our efforts is to explore application formulations, Cloud and hybrid HPC/Grid + Cloud infrastructure usage modes that are meaningful for various classes of science and engineering application workflows.

GreenTouch is a collaborative environment that enables novice users to engage in authentic scientific inquiry. It consists of a mobile user interface for capturing data in the field, a web application for data curation in the cloud, and a tabletop user interface for exploratory analysis of heterogeneous data.

Project description:Teaching Cloud Computing in an Introduction to Engineering class for freshmen. We explore how well-designed systems are built to withstand unpredictable stresses, whether that system is a building, a piece of software or even the human body. The grant from Google is allowing us to add an overview of cloud computing as a platform that is robust under diverse loads.

Project description: By building an online Course Management System, students will be able to work on their team projects in the cloud. The system allows instructors and students to manage the course materials, including course syllabus, slides, assignments and tests in the cloud; the tool can be shared with educational institutions worldwide.

The App Engine team is continuing to make monthly improvements to our platform. We have a number of new features and fixes for this month’s release.

New App Engine billing system for paid applications

We’re making it easier to pay for App Engine each billing cycle by transitioning to a new billing system. This change will happen automatically for billing-enabled applications, with no action required on your part. With the new system you can now:

take advantage of monthly billing cycles

make a payment at any time during the month

specify direct debit as a form of payment

assign a primary and backup credit card

We’ll start moving applications to this new billing system over the next few weeks. You don’t need to make any changes and the migration itself will be transparent.

Other notable features

Full Text Search API stats are now available in the admin console. You can start viewing these stats in advance of being able to pay for additional search resources in an upcoming release.

A major overhaul to the Python dev_appserver, the software used to simulate App Engine while in development. The new dev_appserver is multi-threaded, meaning development is faster, and provides a more accurate simulation of the production environment.

Admin console dashboard charts and current load/errors reports are moving to a new, more reliable backend over the next few weeks.

Improved support for Python libraries, with Django 1.4.2 and webob 1.2.3 now Generally Available.

The complete list of features and bug fixes for 1.7.6 can be found in our release notes. For App Engine coding questions and answers check us out on Stack Overflow, and for general discussion and feedback, find us on our Google Group.

Today’s post comes from Doug Fritz from the Data Arts Team of the Google Creative Lab.In this post, Doug shares a small open source project for reading and writing to the Google App Engine Datastore with JavaScript.

Today, the Google Creative Lab is sharing a small open source project called Tailbone that lets developers read and write to the Google App Engine Datastore using JavaScript. We’re hoping that it makes App Engine a bit more accessible to developers who aren’t familiar with Python, Java or Go, or prefer not to use them.

I share an office with three creative programmers who work almost entirely in HTML5 and JavaScript. An important part of our work is writing server-side code for new projects that read or write data to to the App Engine Datastore or use Google accounts to store authenticated user-specific information. To make that process easier for my JavaScript-fluent colleagues, I created Tailbone to act as a RESTful API for an app’s Datastore.

To get started, you still have to install App Engine’s SDK and Python, but after that you’re all set. We’ve written a detailed tutorial that guides you through the installation and an example app for creating an authenticated profile page with an editable name and photo.

It’s my hope that Tailbone makes App Engine a little bit less intimidating for people who don’t have much experience with server-side coding. I know there are a few in my office. If there are any others out there, this is for you.

Python 2.5 has a special place in the heart of any Google App Engine developer, as it was the first runtime we launched way back in 2008. Since then, both Python and App Engine have advanced a great deal. A year ago we announced our support for Python 2.7, which brings syntactic and semantic improvements to the language and includes powerful features like threading and a large selection of third-party libraries.Not only does Python 2.7 make developers’ lives easier, the runtime is extremely cost-effective. Our customers have taken advantage of features like concurrent requests to reduce their front-end instance costs by more than 70% while handling the same amount of traffic.Not surprisingly, the Python 2.7 runtime has proven to be extremely popular. Just over a year after launch, more than 78% of active Python applications on App Engine are using the new runtime, and more are being added every minute.As both Python and App Engine evolve, we must occasionally make hard choices about which legacy runtimes we should continue to support. Today we are announcing the deprecation of the Python 2.5 runtime. The deprecation period will follow the guidelines set in our terms of service.What does this mean?

We will continue to run Python 2.5 applications throughout the deprecation period. For most customers, upgrading to Python 2.7 is trivial as most elements of Python 2.5 are forwards-compatible with Python 2.7. We’ve prepared a handy migration guide that covers the steps to migrate in detail.

Future versions of the App Engine Python Development SDK will display warnings to developers deploying updates to a deprecated runtime.

Starting from January 2014, we will no longer allow new applications to be created using the Python 2.5 runtime.

We encourage all developers using Python 2.5 to consider migrating as soon as possible. We’re confident that the vast majority of our customers will find the upgrade straightforward and the benefits substantial.If you’re considering migrating, here are some useful resources:

Are you developing on Google App Engine today or interested in learning how to use it? If you’ve gone through all the great App Engine docs and Getting Started tutorials (Python, Java, or Go) but want to take your App Engine skills a step further, then Google Developers Academy (GDA) is the place to go! We launched GDA this past summer at Google I/O 2012, with content for beginners as well as seasoned developers. What can you find on App Engine in GDA today?

If you’re interested in getting more background on what cloud computing is and where App Engine fits into that ecosystem, then this intro class (Introduction to Google App Engine) is for you. Once you’re done with this class, you’ll be ready to tackle the Getting Started tutorial, and after that, move on to the App Engine 101 in Python class.While some of the material found in App Engine 101 is similar to what’s in the Getting Started tutorial, the 101 class targets developers who skipped the tutorial or completed it at some point in the past but don’t want to repeat the exact same thing. The main differences include the following changes to the tutorial’s content:

You can use the relational MySQL-compatible Google Cloud SQL service as an alternative to App Engine’s native non-relational datastore. Some applications do require a relational database, especially if you’re porting an existing app that relies on one. In this case, you want to learn about Cloud SQL and how to use it with App Engine. That’s why we have the Using Python App Engine with Google Cloud SQL class.Of course, Google is best known for search. With App Engine’s powerful Search API, you can index not only plain text, but also HTML, atoms, numbers, dates, and locations (lat/long). Getting Started with the Python Search API is a two-part class that will indeed get you started: in the first part of the class, you’ll create an application using a variety of data and learn how to index such data (using “documents”). In Part 2, you’ll learn how to execute queries as well as how to update your indexes when you modify your data.If variety is what you’re after, then look no further than the newest class in GDA: Getting Started with Go, App Engine and Google+ API. You will not only learn how to create an App Engine app using the Go programming language, but also learn how to connect to the Google+ API with the Google APIs Client Library for Go.These are just a few examples of the types of classes you’ll find in GDA. We also have content that features many other Google technologies, including Android, Chrome, YouTube, Maps, Drive, and Wallet. We invite you to swing by for a visit soon.

Today’s post comes from Jake Moshenko, founder of DevTable. DevTable is a collaborative hosted IDE which aims to provide a single development environment that can be accessed online from any device or location. It also allows you to collaborate on projects in real-time with your teammates. DevTable supports development and deployment of Google App Engine projects in the cloud.At DevTable, we support development of Google App Engine apps with Python directly on the cloud, without having to install and run the App Engine SDK locally. While the App Engine SDK development experience is excellent, it is not yet supported on mobile or web platforms.Some of the major reasons to use DevTable for App Engine are:

Cloud based editing and deployment of your App Engine projects

Autocomplete for Python code, including built-in App Engine libraries

OAuth deployment, so DevTable never has access to your Google Credentials

To get started, first log in to your DevTable account and create a new project using our Google App Engine template. This template loads the basic webapp “hello world” project that you’re probably already familiar with from the App Engine documentation. Follow the instructions to create a new App Engine app and to authorize DevTable to deploy on your behalf. Don’t worry, we use OAuth deployment, which means we will never ask you for your Google password.

Now that you have everything set up, press the Run Project button and select View on App Engine Mimic, which will deploy the Mimic bootstrap code to a special version of your app. This may take up to a few minutes, but each test deploy after this should happen instantaneously. Once Mimic has been deployed, you will see “Hello, world.” proudly displayed in a new browser tab. Each time you refresh this page, the newest code is pulled from your DevTable project, so editing and testing code is seamless. Try it now; change the message in your app’s main .py file, then refresh the tab which is showing your project.

Python autocomplete and documentation in DevTable

Mimic works by creating a proxy which intercepts requests to your app and loads your app code dynamically from the datastore. DevTable keeps this code in sync with your latest changes. One added bonus to testing your code using DevTable and Mimic is that your test code will be running in the production App Engine environment, so some APIs and capabilities will work that don’t work on the Development Server, such as the App Identity API and making multiple concurrent requests.

Mimic bootstrap code deployment

Once you are happy with how your app works in Mimic, you may want to deploy your application to production. Click the Deploy button, to deploy your app directly to App Engine, which may take a few minutes. Once deployment is complete, you can view your app at the production url, which is probably something like .appspot.com.What can you do with this? You can build and deploy apps completely in the cloud. You can use DevTable as an emergency backup editor to check out your code from Git, fix a small bug, and push to production, without having access to your development machine, from the beach! You can use our real-time collaboration support to pair program an App Engine app concurrently across the world. Our users are constantly surprising us with new ways to use DevTable, and we’re excited to see what you can come up with too!We encourage you to get started now building apps using DevTable on App Engine. If you have any questions or suggestions, we are always available at support@devtable.com. Just send us an email and we’ll get back to you as quickly as we can.

One of the most rewarding parts of working on Google App Engine is seeing our developers create groundbreaking new applications on top of our infrastructure. To help our current and prospective users gain insight into the vast array of these applications, we recently added a section to the Google Cloud Platform site with a collection of case studies. Whether you’re interested in learning about how businesses are building on our platform or justlooking for inspiration for your next project, we hope you find these pieces informative.RovioCreator of the blockbuster “Angry Birds” game series used App Engine when creating web versions of their game. They were able to create customized versions of their game in just 2 weeks using App Engine, allowing them to capitalize on opportunities to grow their business.GetAroundTechCrunch Disrupt award-winning car sharing service used App Engine to build a marketplace connecting car owners to people looking to rent cars. They scaled their product without adding additional staff.MAG InteractiveDeveloper of mobile casual games, including the hit game Ruzzle, scaled their backend using App Engine. They grew to over 5 million users, and experienced “no scalability issues at all.”NubbiusThe Cloud Gate used App Engine to create nubbius, a software-as-a-service offering for lawyers to manage their workflow from anywhere. They saved more than $130,000 per year while scaling rapidly.RedBusOnline travel agency used Google BigQuery to unify tens of thousands of bus schedules into a single booking operation. They analyzed data sets as large as 2 TB in less than 30 seconds, and spent 80% less than they would have on a Hadoop infrastructure,This is a sample of the many case studies we have on our site. Check out cloud.google.com/customers to see the full list. You can read about companies varying in size, industry, and use cases, who are using Google Cloud Platform to build their products and businesses.